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Flatten subprojects into a single base monorepo
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---
include: rocblas_common.yaml
include: known_bugs.yaml
Definitions:
- &invalid_size_range
- { M: 3, N: 3, lda: 3, incx: 3, ldc: 3, stride_scale: 1, batch_count: -1 } # batch_count < 0
- { M: -1, N: 1, lda: 1, incx: 1, ldc: 1, stride_scale: 1 } # M < 0
- { M: 1, N: -1, lda: 1, incx: 1, ldc: 1, stride_scale: 1 } # N < 0
- { M: 2, N: 2, lda: 1, incx: 1, ldc: 2, stride_scale: 1 } # lda < M
- { M: 2, N: 2, lda: 2, incx: 1, ldc: 1, stride_scale: 1 } # ldc < M
- &quick_return_size_range
- { M: 3, N: 3, lda: 3, incx: 3, ldc: 3, batch_count: 0 } # batch_count == 0
- { M: 0, N: 1, lda: 1, incx: 1, ldc: 1 } # M == 0
- { M: 1, N: 0, lda: 1, incx: 1, ldc: 1 } # N == 0
- &small_matrix_size_range
- { M: 2, N: 2, lda: 2, incx: 0, ldc: 2 } # incx = 0
- { M: 3, N: 3, lda: 3, incx: -1, ldc: 3 }
- { M: 3, N: 33, lda: 35, incx: 2, ldc: 35 }
- { M: 10, N: 11, lda: 100, incx: 3, ldc: 13 }
- &large_matrix_size_range
- { M: 192, N: 193, lda: 194, incx: 1, ldc: 196 }
- { M: 640, N: 641, lda: 960, incx: -2, ldc: 962 }
- { M: 1001, N: 1000, lda: 1003, incx: 3, ldc: 1001 }
- { M: 2, N: 4300000, lda: 2, incx: 1, ldc: 4 } # Test 16-bit overflow in grid Y
- &huge_matrix_size_range
- { M: 4011, N: 4012, lda: 4012, incx: 2, ldc: 4014 }
Tests:
- name: bad_arg
category: quick
function:
- dgmm_bad_arg
- dgmm_batched_bad_arg
- dgmm_strided_batched_bad_arg
precision: *single_double_precisions_complex_real
side: [R]
api: [ C, FORTRAN ]
- name: invalid_size
category: quick
function:
- dgmm
- dgmm_batched
- dgmm_strided_batched
precision: *single_double_precisions
side: [L]
matrix_size: *invalid_size_range
api: [ C, FORTRAN ]
- name: dgmm_size_t
category: stress
function: dgmm
precision: *single_precision
side: [ L, R ]
matrix_size:
- { M: 2048, N: 2048, lda: 1049100, ldc: 2048, incx: 1}
- { M: 2048, N: 2048, lda: 2048, ldc: 1049100, incx: 1}
- { M: 2048, N: 2048, lda: 2048, ldc: 2048, incx: 1049100 }
batch_count: [ 1 ]
api: C
gpu_arch: ['90a','942','950']
os_flags: LINUX
- name: dgmm_quick_return
category: quick
function: dgmm
precision: *single_double_precisions
side: [L]
matrix_size: *quick_return_size_range
- name: dgmm_batched_quick_return
category: quick
function: dgmm_batched
precision: *single_double_precisions
side: [L]
matrix_size: *quick_return_size_range
- name: dgmm_strided_batched_quick_return
category: quick
function: dgmm_strided_batched
precision: *single_double_precisions
side: [L]
matrix_size: *quick_return_size_range
stride_scale: [ 1]
- name: dgmm_small
category: quick
function: dgmm
precision: *single_double_precisions
side: [L, R]
matrix_size: *small_matrix_size_range
api: [ C, FORTRAN ]
- name: dgmm_batched_small
category: quick
function: dgmm_batched
precision: *single_double_precisions
side: [L, R]
matrix_size: *small_matrix_size_range
batch_count: [ 1, 2 ]
api: [ C, FORTRAN ]
- name: dgmm_strided_batched_small
category: quick
function: dgmm_strided_batched
precision: *single_double_precisions
side: [L, R]
matrix_size: *small_matrix_size_range
stride_scale: [ 1, 2 ]
batch_count: [ 1, 2 ]
api: [ C, FORTRAN ]
- name: dgmm_small_complex
category: quick
function: dgmm
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *small_matrix_size_range
api: [ C, FORTRAN ]
- name: dgmm_batched_small_complex
category: quick
function: dgmm_batched
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *small_matrix_size_range
batch_count: [ 1, 2 ]
api: [ C, FORTRAN ]
- name: dgmm_strided_batched_small_complex
category: quick
function: dgmm_strided_batched
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *small_matrix_size_range
stride_scale: [ 1, 2 ]
batch_count: [ 1, 2 ]
api: [ C, FORTRAN ]
- name: dgmm_large
category: pre_checkin
function: dgmm
precision: *single_double_precisions
side: [L, R]
matrix_size: *large_matrix_size_range
- name: dgmm_large_complex
category: pre_checkin
function: dgmm
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *large_matrix_size_range
- name: dgmm_batched_large_complex
category: pre_checkin
function: dgmm_batched
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *large_matrix_size_range
batch_count: [ 1, 2 ]
- name: dgmm_strided_batched_large_complex
category: pre_checkin
function: dgmm_strided_batched
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *large_matrix_size_range
stride_scale: [ 1, 2 ]
batch_count: [ 1, 2 ]
- name: dgmm_huge
category: nightly
function: dgmm
precision: *single_double_precisions
side: [L, R]
matrix_size: *huge_matrix_size_range
- name: dgmm_huge_complex
category: nightly
function: dgmm
precision: *single_double_precisions_complex
side: [L, R]
matrix_size: *huge_matrix_size_range
- name: dgmm_large_batch
category: pre_checkin # TODO
arguments:
- { M: 2, N: 2, lda: 2, ldb: 2, ldc: 2, incx: 1, batch_count: *c_grid_yz_require_passes }
side: [L, R]
function:
- dgmm_batched: *single_precision
- dgmm_strided_batched: *single_precision
stride_scale: 1
- name: dgmm_ILP64
category: stress
arguments:
- { M: 2147483649, N: 1, lda: 2147483649, incx: 1, ldc: 2147483649, batch_count: 1 }
- { M: 1, N: 2147483649, lda: 1, incx: 1, ldc: 1, batch_count: 1 }
- { M: 1, N: 1, lda: 1, incx: -2147483649, batch_count: 1 }
- { M: 2, N: 2, lda: 4, incx: 2, batch_count: *c_grid_yz_require_passes }
api: [ C_64 ]
side: [L, R]
os_flags: [ LINUX ]
function:
- dgmm: *single_precision
stride_scale: 1
gpu_arch: '9??'
- name: dgmm_graph_test
category: pre_checkin
function:
- dgmm
- dgmm_batched
- dgmm_strided_batched
precision: *single_double_precisions_complex
side: [L]
matrix_size:
- {M: 3, N: 33, lda: 35, incx: 2, ldc: 35 }
stride_scale: [ 1 ]
batch_count: [ 2 ]
graph_test: true
- name: dgmm_repeatability_check
category: stress
function:
- dgmm
- dgmm_batched
- dgmm_strided_batched
precision: *single_double_precisions_complex
side: [L]
matrix_size:
- {M: 3, N: 33, lda: 35, incx: 2, ldc: 35 }
stride_scale: [ 1 ]
batch_count: [ 2 ]
atomics_mode : 0
initialization: hpl
pointer_mode_host: false
iters : 5
devices: 4
repeatability_check: true
...
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